No abstract

Video imagery was examined to quantify seafloor disturbance and damage to corals and sponges relative to fishing practices in the central Aleutian Islands of Alaska. Corals and sponges were classified as damaged if they had broken skeletons, missing or broken branches, were torn (i.e. sponges) or detached from the seafloor, or were attached but lying on the seafloor. Disturbance was defined as any alteration to the seafloor or biota caused by fishing gear or natural events. Overall, 14% of corals and 21% of sponges were damaged, and disturbance was widespread and evident on most video transects. The proportion of damaged corals was significantly less (p = 0.003) in areas with little or no bottom trawl fishing versus areas with medium and high intensity bottom trawl fishing. For other gear types, damage was not significantly different among fishing levels. Damage for all corals was 7% in untrawled areas, 7% in low-intensity areas, 14% in medium-intensity areas, and 49% in high-intensity areas. For gorgonians, 5% were damaged in untrawled areas and 23% were damaged in high-intensity areas. For hydrocorals, damage was 10% in untrawled areas and 53% in medium-intensity areas. Hydrocorals were absent from high-intensity areas. About 40% of sea whips were damaged in high-intensity areas versus 1% in other areas. While some protective measures have been implemented to halt the expansion of bottom trawl fishing to unfished areas, the conservation of coral and sponge habitat in fished areas is still of primary concern.KEY WORDS: Deep-sea coral · Sponge · Damage · Habitat · Fishing gear effects Resale or republication not permitted without written consent of the publisher Contribution to the Theme Section 'Conservation and management of deep-sea corals and coral reefs'OPEN PEN

No abstract

No abstract

No abstract

Abstract-Collecting age-composition data is a critical aspect of stock assessment; however, there are no biological or statistical investigations that support optimization of the distribution of sample size across species. Sample sizes for both collection and age-reading are often set by using ad hoc or historical values. Investigations into quantifying the trade-offs when allocating sample sizes across species are needed because resources for age determination are always limited. In this study we performed analyses to investigate the distribution of sample sizes to determine ages across multiple species by using methods derived from sampling theory and simulation testing of stock assessment models. We found that, in terms of methods based on sampling theory, distribution of sample size under 2-stage sampling could be significantly related to the life-history characteristics of the species. Results from simulation analysis illustrated that the influence of sample sizes required to determine age composition of fish on uncertainty in stock assessment models was related to uncertainty in a survey index and recruitment variability of the species being assessed. The simulation analysis highlighted cases in which larger age-composition sample size did not appreciably decrease uncertainty in the stock assessment model, in particular, for species with lower recruitment variability and larger survey index uncertainty.

We demonstrate the process of synchronously combining multiple sources of available fishery information to estimate total abundance in data‐limited situations. The application is specific to semelparous populations, such as Pacific salmon, where only data for spawners and recruits are necessary to describe the dynamics of these populations. We apply this technique to summer chum salmon Oncorhynchus keta of the Kuskokwim and Yukon rivers of Alaska. Since 1997, low numbers of returning chum salmon to these rivers have resulted in low harvests, with significant negative economic and social impacts to rural residents of the region. The existing programs for assessing salmon stock in these river basins are inadequate for conventional estimates of total run abundance and the modeling of stock dynamics necessary to derive a quantitative assessment of the returns. Our approach was to utilize the pattern extraction qualities of principal components analysis (PCA) to estimate the underlying trend in escapement. We then combined this index with other available fishery data in a maximum likelihood statistical framework, weighting the data sets according to their quality. Using this methodology, we derived indices of chum salmon abundance and escapement for the Kuskokwim and Yukon rivers. Data sources included commercial catch and effort, escapement surveys, test fishery catch rates, and whole‐river sonar counts. Error estimates of the time series of abundance and escapement as well as of the model parameters were generated by bootstrap methods. We found that several parameters of the model were confounded without some independent measure of total abundance or escapement. We also determined that the escapement trend estimated by PCA was consistent over a large geographic area, suggesting that survival was predominantly influenced by conditions where the fish share a common environment. We suggest that our methodology may be appropriate to other regions and different semelparous species.

No abstract